bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.12.06.519263

Matrix Gla Protein acts as a driver of stemness and tumor initiation in ovarian cancer

Nieddu, V.·Melocchi, V.·Battistini, C.·Franciosa, G.·Lupia, M.·Stellato, C.·Bertalot, G.·Olsen, J. V.·Colombo, N.·Bianchi, F.·Cavallaro, U.
View original source ↗Export metadata ↓

Abstract

Ovarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential. We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings. Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.

Source connections

Explore related subjects

cancer biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nieddu, V., Melocchi, V., Battistini, C., Franciosa, G., Lupia, M., Stellato, C., Bertalot, G., Olsen, J. V., Colombo, N., Bianchi, F., Cavallaro, U.. 2022-12-08. Matrix Gla Protein acts as a driver of stemness and tumor initiation in ovarian cancer. https://doi.org/10.1101/2022.12.06.519263

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

m6A-Driven Intratumoral Cholesterol Biosynthesis Fuels Castration-Resistant Prostate Cancer Progression

Both nuclear pore complexes (NPCs) and RNA N6-methyladenosine (m6A) machinery are indispensable for proper cellular function. Although their collaborative roles in the nuclear export of messenger RNAs (mRNAs) have been reported, it remains ambiguous whether and how this collaboration may contribute to cancer progression. Here we identify a functional cooperation between NPCs and m6A signaling that promotes the development of castration-resistant prostate cancer (CRPC). We showed that nuclear export of m6A-modified mRNAs, mediated by the interaction between RNA methyltransferase METTL3 and the nucleoporin NUP93, is functionally coupled to cholesterol biosynthesis. Given that cholesterol-fueled intratumoral androgen production is one of the mechanisms driving CRPC, we demonstrated that overexpression of the wild-type METTL3 or NUP93, but neither the enzymatically dead METTL3 nor the mutant NUP93 that loses METTL3-interacting capability, elevates intracellular levels of androgens, activates AR signaling under castrate condition, and promotes androgen-independent growth of prostate cancer cells both in vitro and in vivo. Importantly, pharmacological inhibition of METTL3 or targeted demethylation on mRNAs encoding key cholesterol biosynthesis enzymes effectively suppressed CRPC malignancy. Together, these findings uncover a therapeutically targetable m6A-METTL3-NUP93 axis that links nuclear mRNA export and metabolic reprogramming to fuel CRPC progression, providing a conceptually new strategy for the treatment of this lethal disease.

cancer biology↗
bioRxiv2026

ST6Gal2 promotes α2,6-sialylation and aggressive phenotypes in neuroblastoma cells

Neuroblastoma is the most common extracranial solid tumor of childhood. Its clinical behavior ranges from spontaneous regression to lethal, treatment-refractory disease. Aberrant 2,6-sialylation contributes to aggressive phenotypes in many cancers, but the role of ST6Gal2, a neural-enriched 2,6-sialyltransferase, in neuroblastoma is largely unexplored. Here, we examine the clinical and functional significance of ST6Gal2 in neuroblastoma. In two independent public cohorts (SEQC, n=498; Kocak, n=649), high ST6GAL2 expression was associated with significantly worse overall and event-free survival. In the SEQC cohort, ST6GAL2 expression was higher in high-risk and MYCN-amplified tumors, varied across International Neuroblastoma Staging System stages, and correlated positively with a mesenchymal transcriptional signature (Spearman {rho}=0.181). The mesenchymal correlation was reproduced in the Kocak cohort ({rho}=0.204). Stable shRNA-mediated knockdown of ST6GAL2 in SK-N-AS and SK-N-BE(2) cells reduced proliferation and viability, impaired wound closure, and decreased migration and invasion. In preliminary experiments in SK-N-AS cells, ST6GAL2 knockdown reduced binding of Sambucus nigra agglutinin, consistent with a role for ST6Gal2 in 2,6-sialylation. Together, these findings link ST6Gal2 expression to aggressive clinical and transcriptional features and pro-tumorigenic phenotypes in neuroblastoma and nominate ST6Gal2-mediated sialylation as a candidate pathway for mechanistic study.

cancer biology↗
bioRxiv2026

Unsupervised transcriptomic analysis of paired pre- and post-treatment specimens reveals divergent chemoimmunomodulatory induction trajectories in breast cancer

The immunomodulatory effects of chemotherapy (chemoimmunomodulation; CIM) are clinically consequential and heterogeneous, yet no systematic framework exists for classifying the immunomodulatory trajectory a tumor follows in response to treatment (CIM trajectory). Here, we present the CIM Induction Classifier (CIMIC), an unsupervised clustering pipeline leveraging delta gene expression across 3,189 CIM-related genes to classify specimens chemoimmunomodulatory trajectory. Applied to two pre- and post-chemotherapy breast cancer (BC) datasets (NKI/SMC, N = 36; NEO, N = 19) and nine epirubicin-perturbed triple-negative BC (TNBC) cell lines, CIMIC identified two divergent CIM trajectories: a functional CIM (Fun-CIM) trajectory, broadly conserved across tumors and cell lines and characterized by induction of inflammatory cell death, antigen presentation, viral mimicry, and adaptive immune activation programs, and a dysfunctional CIM (Dys-CIM) trajectory, characterized by induction of proteostatic and metabolic stress-adaptation programs, reduced immune cell abundances and cytotoxic activity, and enrichment of aggressive BC subtypes. Using survival and longitudinal transcriptomic data in NKI/SMC (N = 20), treatment-induced increases in Fun-CIM-associated genes and ssGSEA scores were associated with reduced recurrence, whereas Dys-CIM-associated genes and scores were associated with increased recurrence. In multivariable analyses within independent chemotherapy-treated BC cohorts (METABRIC, N = 412; SCAN-B, N = 2,462), higher baseline Fun-CIM ssGSEA scores were associated with better outcomes, whereas higher baseline Dys-CIM ssGSEA scores were associated with worse outcomes. These findings establish CIM as a dynamic, trajectory-level process and position CIMIC as a framework for defining CIM trajectories and supporting future efforts to identify predictors, mechanisms, and therapeutic strategies that maximize beneficial CIM.

cancer biology↗